Bachelor's Degree or Master's Degree in a relevant field of study.

6-8 years of experience in data science or related roles.

Develop, finetune, and evaluate LLMbased models (e.g. GPT, Gemini, Claude, DeepSeek, Mistral).

Implement retrievalaugmented generation (RAG) pipelines using vector databases and embedding models.

Design and iterate prompts, system instructions, templates, and chains of reasoning to improve output quality.

Develop automated prompt evaluation frameworks using offline metrics and humanintheloop reviews.

Optimize prompts for stability, safety, and enterprisegrade reliability.

Expertise in programmingbased analytics with experience in two or more of the following: SQL, Python, LLM prompt engineering.

Proven experience in building statistical models, segmentation, and predictive or propensity models (e.g. clustering, predictive modeling, neural networks, scenario analysis, conceptual modeling, and hypothesis testing).

Strong understanding of machine learning algorithms, design principles, and best practices.

Solid understanding of machine learning model management principles and practices.

Ability to work in a fastpaced, multidisciplinary, and competitive environment.

Strong analytical, deductive reasoning, problemsolving, and criticalthinking skills.

Strong collaboration skills with the ability to work effectively across teams.

Strong business acumen and project management skills, with the ability to manage multiple priorities.

Added advantage if the candidate has experience with Big Data platforms (especially unstructured data) and deep learning.

Strong sense of urgency and accountability to drive business outcomes.